JADE-DR-VPP is an open-source Java framework that implements a multi-agent system for Virtual Power Plant (VPP) demand response (DR). Each agent represents a flexible load or generation unit that communicates via JADE messaging. The system orchestrates DR events, schedules load adjustments, and aggregates resources to meet grid signals. Users can configure agent behaviors, run large-scale simulations, and analyze performance metrics for energy management strategies.

Multi-Agent Systems provides a comprehensive toolkit for creating, controlling, and observing interactions among autonomous agents. Developers can define agent classes with custom decision-making logic, set up complex environments with configurable resources and rules, and implement communication channels for information exchange. The framework supports synchronous and asynchronous scheduling, event-driven behaviors, and integrates logging for performance metrics. Users can extend core modules or integrate external AI models to enhance agent intelligence. Visualization tools render simulations in real-time or post-process, helping analyze emergent behaviors and optimize system parameters. From academic research to prototype distributed applications, Multi-Agent Systems simplifies end-to-end multi-agent simulations.

AgentSimJS is designed to simplify the creation and execution of large-scale agent-based models in JavaScript. With its modular architecture, developers can define agents with custom states, sensors, decision-making functions, and actuators, then integrate them into dynamic environments parameterized by global variables. The framework orchestrates discrete time-step simulations, manages event-driven messaging between agents, and logs interaction data for analysis. Visualization modules support real-time rendering using HTML5 Canvas or external libraries, while plugins enable integration with statistical tools. AgentSimJS runs both in modern web browsers and Node.js, making it suitable for interactive web applications, academic research, educational tools, and rapid prototyping of swarm intelligence, crowd dynamics, or distributed AI experiments.

ASP-DALI provides a unified platform for defining and executing logic-based intelligent agents. Developers write ASP rules to represent agent knowledge and goals, while DALI constructs define event reactions and action executions. At runtime, an ASP solver computes answer sets that guide the agent’s decisions, enabling it to plan, react to incoming events, and adjust beliefs dynamically. The framework supports modular knowledge bases, facilitating incremental updates and clear separation between declarative rules and reactive behaviors. ASP-DALI is implemented in Prolog with interfaces to popular ASP solvers, simplifying integration and deployment across research and prototype scenarios.